Switching Time Optimization for Binary Quantum Optimal Control

TL;DR

This paper introduces a novel algorithmic framework for optimizing binary quantum control switches and durations, improving control quality and computational efficiency in diverse quantum applications.

Contribution

It develops a sequential optimization approach combining relaxation, heuristics, and switching time optimization for binary quantum control problems.

Findings

High-quality binary control solutions achieved

Reduced computational time demonstrated

Effective across various quantum physics applications

Abstract

Quantum optimal control is a technique for controlling the evolution of a quantum system and has been applied to a wide range of problems in quantum physics. We study a binary quantum control optimization problem, where control decisions are binary-valued and the problem is solved in diverse quantum algorithms. In this paper, we utilize classical optimization and computing techniques to develop an algorithmic framework that sequentially optimizes the number of control switches and the duration of each control interval on a continuous time horizon. Specifically, we first solve the continuous relaxation of the binary control problem based on time discretization and then use a heuristic to obtain a controller sequence with a penalty on the number of switches. Then, we formulate a switching time optimization model and apply sequential least-squares programming with accelerated time-evolution simulation to solve the model. We demonstrate that our computational framework can obtain binary controls with high-quality performance and also reduce computational time via solving a family of quantum control instances in various quantum physics applications.